iPhone 16 Pro Max
Geekbench AI Score
3928
Single Precision Score
32508
Half Precision Score
44773
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | September 22 2025 09:19 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A18 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.0 |
| Model | iPhone 16 Pro Max |
| Model ID | iPhone17,2 |
| Motherboard | D94AP |
| CPU Information | |
|---|---|
| Name | Apple A18 Pro |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 4.04 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 7.44 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1929
358.7 IPS |
|
|
Image Classification (HP)
|
100% |
14746
2.74 KIPS |
|
|
Image Classification (Q)
|
97% |
19234
3.59 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1592
25.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
17309
280.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
22287
361.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
7547
8.81 IPS |
|
|
Pose Estimation (HP)
|
100% |
140939
164.5 IPS |
|
|
Pose Estimation (Q)
|
95% |
286190
335.4 IPS |
|
|
Object Detection (SP)
|
100% |
1937
153.6 IPS |
|
|
Object Detection (HP)
|
100% |
15376
1.22 KIPS |
|
|
Object Detection (Q)
|
91% |
21146
1.69 KIPS |
|
|
Face Detection (SP)
|
100% |
3073
36.5 IPS |
|
|
Face Detection (HP)
|
100% |
38680
459.6 IPS |
|
|
Face Detection (Q)
|
100% |
53362
634.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
7037
54.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
86889
669.4 IPS |
|
|
Depth Estimation (Q)
|
85% |
157733
1.23 KIPS |
|
|
Style Transfer (SP)
|
100% |
15406
19.8 IPS |
|
|
Style Transfer (HP)
|
100% |
241187
310.0 IPS |
|
|
Style Transfer (Q)
|
96% |
293237
378.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4661
172.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
51470
1.90 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
81768
3.02 KIPS |
|
|
Text Classification (SP)
|
100% |
3742
5.00 KIPS |
|
|
Text Classification (HP)
|
99% |
6582
8.79 KIPS |
|
|
Text Classification (Q)
|
93% |
6381
8.56 KIPS |
|
|
Machine Translation (SP)
|
100% |
3354
57.8 IPS |
|
|
Machine Translation (HP)
|
100% |
8678
149.5 IPS |
|
|
Machine Translation (Q)
|
98% |
9690
167.5 IPS |
